11.25 Flipped Mean Confidence Intervals
20200822
%>%
ds filter(location %in% (ds$location %>% unique %>% sample(20))) %>%
mutate(location=factor(location,
levels=location %>% unique() %>%
sort() %>% rev())) %>%
ggplot(aes(location, temp_3pm, fill=location)) +
stat_summary(fun="mean", geom="bar") +
stat_summary(fun.data="mean_cl_normal", geom="errorbar", width=0.35) +
theme(legend.position="none") +
labs(x=vnames["temp_3pm"], y=vnames["location"]) +
coord_flip()
Various annotations can be added to plots. In this example we include a confidence interval around the average values.
Your donation will support ongoing development and give you access to the PDF version of the book. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Popular open source software includes rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984.
Copyright © 1995-2021 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0.